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| Content Provider | Springer Nature Link |
|---|---|
| Author | Halawana, Hachem Hamdan, Hani Hamdan, Mohamad |
| Copyright Year | 2010 |
| Abstract | Most stereo algorithms are based only on an analysis of the luminance information. However, with advances in camera technology, in addition to the fact that color information can robustly improve matching, color stereovision is receiving more and more attention. Color stereovision setups are usually based on single-sensor cameras which provide color filter array (CFA) images. In these images, a single color component is sampled at each pixel rather than the three required components red, green, and blue (RGB). We show that standard demosaicing techniques, which are used to interpolate the missing components, are not well adapted when the resulting color pixels are matched in order to estimate image disparities. In order to avoid this problem while exploiting color information, we propose a new matching system designed for dense stereovision based on pairs of CFA images. |
| Starting Page | 508 |
| Ending Page | 511 |
| Page Count | 4 |
| File Format | |
| ISSN | 14335298 |
| Journal | Artificial Life and Robotics |
| Volume Number | 15 |
| Issue Number | 4 |
| e-ISSN | 16147456 |
| Language | English |
| Publisher | Springer Japan |
| Publisher Date | 2011-12-28 |
| Publisher Place | Japan |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Stereovision Demosaicing Matching cost Control, Robotics, Mechatronics Computation by Abstract Devices Artificial Intelligence (incl. Robotics) |
| Content Type | Text |
| Subject | Artificial Intelligence Biochemistry, Genetics and Molecular Biology |
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